Econometrics Instructor

Alignerr Corp.; Cape Town; Remote; ZAR 914,000 - 1,714,000; Part time

Benefits offered by this job

Fully remote

Freelance autonomy

Global collaboration

Job summary

Alignerr is seeking experienced econometrics instructors to help shape how AI understands and explains statistical reasoning. Your expertise will influence AI models trained on econometric content, impacting how AI tackles causal inference, regression, and quantitative analysis.

We invite candidates with 3+ years of university-level econometrics teaching and hands-on experience with R, Stata, or Python. This remote, hourly/task-based role offers 10-40 hours/week and flexible scheduling to

Qualifications

• 3+ years of teaching econometrics or quantitative economics at college/university level
• Strong command of regression analysis, causal inference, and statistical methods
• Able to articulate and evaluate quantitative reasoning clearly

Responsibilities

• Review econometric questions, models, and explanations used in AI training datasets
• Assess statistical accuracy, assumptions, and interpretation of results
• Identify errors and edge cases in AI-generated econometric content
• Provide clear, structured feedback to improve model reasoning and explanations
• Apply teaching and research experience to raise AI output standards
• Work independently and asynchronously on your schedule

Skills

Econometrics

Regression analysis

Causal inference

Statistics

Education

Master's or PhD in Economics, Statistics, or related field

Tools

R

Stata

Python

Job description

About The Role

We're looking for experienced econometrics instructors and quantitative economists to help shape how AI understands and explains statistical reasoning. Your deep subject matter expertise will directly influence the quality of AI models trained on econometric content - making a real impact on how the next generation of AI tackles causal inference, regression, and quantitative analysis.

• Organization: Alignerr (Powered by Labelbox)
• Type: Hourly / Task-based Contract
• Location: Remote
• Commitment: 10-40 hours/week

Econometrics Instructor (AI Training)

About The Role

We're looking for experienced econometrics instructors and quantitative economists to help shape how AI understands and explains statistical reasoning. Your deep subject matter expertise will directly influence the quality of AI models trained on econometric content - making a real impact on how the next generation of AI tackles causal inference, regression, and quantitative analysis.

• Organization: Alignerr (Powered by Labelbox)
• Type: Hourly / Task-based Contract
• Location: Remote
• Commitment: 10-40 hours/week

What You'll Do

• Review and validate econometric questions, models, and explanations used in AI training datasets
• Assess statistical accuracy, underlying assumptions, and interpretation of quantitative results
• Identify errors, edge cases, and misleading reasoning in AI-generated econometric content
• Provide clear, structured feedback to improve model reasoning and explanation quality
• Apply your real-world teaching and research experience to raise the bar for AI output
• Work independently and asynchronously on a schedule that fits your life

Who You Are

• 3+ years of experience teaching econometrics or quantitative economics at a college or university level
• Strong command of regression analysis, causal inference, and statistical methods
• Able to clearly articulate and critically evaluate quantitative reasoning
• Comfortable reviewing structured, technical content with precision and consistency
• Self-motivated and reliable when working independently

Nice to Have

• Master's or PhD in Economics, Statistics, or a related field
• Hands-on experience with statistical tools such as R, Stata, or Python
• Familiarity with AI model evaluation or data annotation workflows

Why Join Us

• Work on cutting-edge AI projects with top research labs
• Fully remote and flexible - work on your own schedule
• Freelance perks: autonomy, variety, and global collaboration
• Get rare, behind-the-scenes exposure to how large language models are trained and evaluated
• Contribute to meaningful work that improves how AI handles complex quantitative reasoning
• Potential for ongoing work and contract extension